Big data analytics refers to the analysis of data of enormous size.

Collecting, cleaning, mining, analyzing, etc. of bigdatabigdata, big data are mainly data collection, data storage, data management, and data analysis and mining technology:

Data processing: natural language processing technology.

Statistical analysis: hypothesis testing, significance testing, difference analysis, correlation analysis, multiple regression analysis, stepwise regression, regression prediction and residual analysis.

Data Mining: Classification, Estimation, Prediction, Affinity grouping or association rules, Clustering. Clustering), Description and Visualization), Complex Data Type Mining (Text, Web, Graphical Image, Video, Audio, etc.).

With the development of big data, big data analytics is widely used in various industries, among which the financial and retail industries are more widely used.

Big Data Analytics Methods:

Big Data Mining: Define the Goal and Analyze the Problem

Before you start big data processing, you should define the goal of processing the data before you can start data mining.

Big Data Mining: Build Models and Collect Data

You can build corresponding data mining models through web crawlers, or data information from previous years, and then collect data to get a large amount of raw data.

Big Data Mining: import and prepare data

After the tools or scripts, the raw is converted into data that can be processed,

Big Data Analysis Algorithms: Machine Learning

By using the method of machine learning, the collected data is processed. Depending on the specific problem. The methods here are particularly varied.

Big Data Analytics Goal: Semantic Engine

Processing big data often uses a lot of time and spends a lot of time, so every time after the generated report, it should support the speech engine function.

Big Data Analytics Goal: Generate visual reports for manual analysis

Through software, a large amount of data is processed and the results are visualized.

Big Data Analytics Goal: Predictive

Through big data analytics algorithms, certain inferences should be made about the data so that the data is more instructive.